Gray correlation of China’s logistics capability and the growth of agriculture economy

2014 ◽  
pp. 325-328
Keyword(s):  
Gray Correlation ◽  
Logistics Capability

scholarly journals A reservoir quality evaluation approach for tight sandstone reservoirs based on the gray correlation algorithm: A case study of the Chang 6 layer in the W area of the as oilfield, Ordos Basin

2021 ◽  
pp. 014459872199851
Author(s):  
Yuyang Liu ◽  
Xiaowei Zhang ◽  
Junfeng Shi ◽  
Wei Guo ◽  
Lixia Kang ◽  
...  
Keyword(s):  
Quality Evaluation ◽  
Comprehensive Evaluation ◽  
Ordos Basin ◽  
Reservoir Quality ◽  
Pore Throat ◽  
Tight Sandstone ◽  
Evaluation Approach ◽  
Correlation Algorithm ◽  
Gray Correlation ◽  
Sandstone Reservoir

As an important type of unconventional hydrocarbon, tight sandstone oil has great present and future resource potential. Reservoir quality evaluation is the basis of tight sandstone oil development. A comprehensive evaluation approach based on the gray correlation algorithm is established to effectively assess tight sandstone reservoir quality. Seven tight sandstone samples from the Chang 6 reservoir in the W area of the AS oilfield in the Ordos Basin are employed. First, the petrological and physical characteristics of the study area reservoir are briefly discussed through thin section observations, electron microscopy analysis, core physical property tests, and whole-rock and clay mineral content experiments. Second, the pore type, throat type and pore and throat combination characteristics are described from casting thin sections and scanning electron microscopy. Third, high-pressure mercury injection and nitrogen adsorption experiments are optimized to evaluate the characteristic parameters of pore throat distribution, micro- and nanopore throat frequency, permeability contribution and volume continuous distribution characteristics to quantitatively characterize the reservoir micro- and nanopores and throats. Then, the effective pore throat frequency specific gravity parameter of movable oil and the irreducible oil pore throat volume specific gravity parameter are introduced and combined with the reservoir physical properties, multipoint Brunauer-Emmett-Teller (BET) specific surface area, displacement pressure, maximum mercury saturation and mercury withdrawal efficiency parameters as the basic parameters for evaluation of tight sandstone reservoir quality. Finally, the weight coefficient of each parameter is calculated by the gray correlation method, and a reservoir comprehensive evaluation indicator (RCEI) is designed. The results show that the study area is dominated by types II and III tight sandstone reservoirs. In addition, the research method in this paper can be further extended to the evaluation of shale gas and other unconventional reservoirs after appropriate modification.

Blockchain technology for port logistics capability: Exclusive or sharing

2021 ◽  
Vol 149 ◽  
pp. 347-392
Author(s):  
Junjin Wang ◽  
Jiaguo Liu ◽  
Fan Wang ◽  
Xiaohang Yue
Keyword(s):  
Blockchain Technology ◽  
Port Logistics ◽  
Exclusive Or ◽  
Logistics Capability

Multiple performance characteristic index optimization of dimensional accuracy and geometrical shape angle in turn-mill multitasking machining

2021 ◽  
pp. 095440542110285
Author(s):  
Wei-Tai Huang ◽  
Shih-Cheng Yang ◽  
Wen-Hsien Ho ◽  
Jinn-Tsong Tsai
Keyword(s):  
Performance Characteristic ◽  
Fuzzy Theory ◽  
Dimensional Accuracy ◽  
Processing Parameters ◽  
Geometrical Shape ◽  
Characteristic Index ◽  
Control Factors ◽  
Experimental Sequence ◽  
Gray Correlation ◽  
Robust Process

Multiple performance objectives in turn-mill multitasking machining are investigated using the Taguchi method combined with the fuzzy theory. Using these two methods, optimized processing parameters can be rapidly identified to obtain optimized dimensional accuracy and geometrical shape angle, thus reducing machining cost and time. Herein, control factors for determining the single objective optimization parameter using the Taguchi robust process L9(34) orthogonal table were spindle speed (rpm), feed (mm/min), C-axis brake pressure (kg/cm2), axial cutting depth (mm), with dimensional accuracy and geometrical shape angle as objective characteristics. Then, signal-to-noise ratios of different groups were generated by gray correlation according to the experimental sequence to obtain the gray correlation coefficient for the calculation of the multiple performance characteristic index (MPCI). The MPCI results demonstrated that optimized dimensional accuracy was 0.005 mm and optimized geometrical shape angle was 0.004°. The optimized MPCI parameters were A3 (4000 rpm), B3 (250 mm/min), C3 (30 kg/cm2), and D3 (1.5 mm). It can reduce the processing for burr elimination and tool wear reduction by MPCI optimized process parameters.

Regional effect of monetary policy based on GVAR model and machine learning

2020 ◽  
pp. 1-13
Author(s):  
Zengming Zhao ◽  
Wenting Chen
Keyword(s):  
Machine Learning ◽  
Growth Rate ◽  
Monetary Policy ◽  
Stress Test ◽  
Analysis Model ◽  
Conduction Model ◽  
Regional Effect ◽  
Macroeconomic Factors ◽  
Model Based ◽  
Gray Correlation

Monetary policy is an important means for a country to regulate macroeconomic operations and achieve established economic goals. Moreover, a reasonable monetary policy improves the efficiency of financial operations on a global scale and effectively resolves the financial crisis. At present, scholars from various countries have begun to pay attention to the issue of differentiated formulation of monetary policy among regions. This paper combines machine learning to construct a monetary policy differentiation effect analysis model based on the GVAR model. Moreover, this paper uses the gray correlation analysis method to obtain the gray correlation matrix between industries, and then introduces the industry’s own characteristics, industry relevance and macroeconomic factors into the macro stress test of credit risk. In addition, this paper constructs a conduction model based on the industry GVAR model, and uses the first-order difference sequence of GDP growth rate, CPI growth rate and M2 growth rate of each economic region to construct a GVAR model to test the impulse response function. The results of the test show that the monetary policy shocks of various economic regions are significantly different. All in all, the research results show that the performance of the model constructed in this paper is good.

Spatial Load Forecasting Based on Load Forecasting Reliability

2014 ◽  
Vol 672-674 ◽  
pp. 1075-1080 ◽  
Author(s):  
Bai Xiao ◽  
Hao Wang ◽  
Gang Mu
Keyword(s):  
Power Supply ◽  
Load Forecasting ◽  
Forecasting Error ◽  
Comprehensive Index ◽  
Gray Correlation Degree ◽  
Analysis Theory ◽  
Correlation Degree ◽  
Forecasting Method ◽  
Gray Correlation

A spatial load forecasting method based on reliability of load forecasting is proposed. It calculates the correlation of wave comprehensive index, variance, maximum predictable ability of each power supply small area’s historical load data by using the analysis theory of grey degree based on the analysis of load forecasting error last target year. The weight of each factor effected on prediction outcomes according to the gray correlation degree is determined, then the load forecasting reliability model of each power supply area is constructed. Finally, by using the adjustment role of load forecasting reliability, the load of target year is forecasted. Actual example shows that the spatial load forecasting method based on reliability of load forecasting is correct and effective.

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